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By L. F. Reinartz

ANOTHER year has rolled by. We are twelve months further away from the start of the depression and. therefore that much nearer to recovery. The accumulated needs and wants 'of our lame, virile population are ready to burst their bonds as soon as confidence returns and credit is stabilized. The steel industry has been harassed by uncertainty of the Government's attitude toward organized labor's de¬mands, and irregularity in volume of production. Steel labor, if left to its own devices, would in most instances, march shoulder to shoulder with the management of steel plants in their effort to pull the industry nut of the ?red.? Cooperation between management and men has improved considerably during; the year.

Jan 1, 1935

By Marcus Weldon

We are at the beginning of an era of profound transformation and human progress — a new industrial revolution. This “Automation of Everything” era will be brought about by digital interfaces, data analysis and control of the physical world through networks employing the Nokia Bell Labs Future X1 architecture — networks to support the digitization and connection of everything and everyone with the goal of automating much of life. The interconnection of robots, machines, drones, sensors, processing platforms and people through Future X networks will provide transformative tools for the automation and optimization of factories and warehouses, ports, electric grids, transportation networks, food, healthcare, construction, logistics and supply chain, emergency response, mining, and other physical industries. To date, the level of automation has been modest at best. Automating these physical industries — industries that account for 70 percent of the US Gross Domestic Product, for example — has the potential to drive significant increases in the world’s economic productivity.2 Realizing the potential of this next industrial revolution will require billions of wirelessly connected endpoints for high fidelity physical-to-digital conversion, millisecond response times to tightly control and coordinate machines and robots, and intelligent analysis to optimize real-time decisions — tasks beyond the reach of current networks. Increased levels of automation are already being achieved through the use of 4G advanced wireless access technologies. The untethering of sensors and actuators in industrial environments through the low-latency, high-bandwidth, high-reliability, and massive scale provided by 5G wireless access will complete this evolution, providing an unprecedented ability to digitize, analyze, comprehend and manipulate the physical world at a scale never previously thought possible. These new capabilities will enable us to create digital models of the physical world with ever higher levels of fidelity, further enhancing our ability to improve operational efficiencies and increase productivity and worker safety. Doing this will require a dramatic evolution in network architecture toward massively distributed cloud control and baseband capacity to achieve the required ultra-low latency and ultra-high bandwidth for industrial and infrastructure automation services — the Future X architecture. In early 2019, Nokia Bell Labs will publish a sequel to “The Future X Network: A Bell Labs Perspective”. “Future X for Industries: A Nokia Bell Labs Perspective” will explore how the Future X architecture will automate many of the world’s physical industries, including chapters devoted to electric power, cities, rail, mining, public safety, manufacturing, ports, logistics and supply chain, and an overarching chapter devoted to securing this highly automated world. To give you a small taste of the feast that’s to come, we’re sharing with you an initial installment — “Future X for Industries: Mining” — the Nokia Bell Labs view of how mining will be transformed through a Future X architecture..

Oct 1, 2019

By Lynn B. Hales

There is a large economic opportunity associated with improving metallurgical performance in mineral processing plants that use process control. Thus, future control systems will be developed towards more sophisticated user friendly, computer-based systems that use powerful software analysis and control techniques. Auto-tuning, adaptive control and process models will gain expanded use because of their transparent availability to the system designer. Control of individual unit operations will be optimized and coordinated through expert systems that monitor economic conditions and management directives and direct operations accordingly. Plant areas, once considered cost centers, will be integrated into plant-wide control systems for economic control and optimization. This article looks at new control hardware, process sensors, control strategies and software development tools. It also looks at the economics driving the continued development of advanced process control systems. Process control systems routinely used in the mining industry were born when the microprocessor was invented. They have continued along an evolutionary path from vendor specific processing hardware and proprietary operating systems to computer industry standard "open architecture" systems. The many economic forces that drive the development and functionality of these process control systems will cause this evolutionary process to continue. Two of the broadest categories are the needs of the end users and the desire of the system manufacturers to distinguish their products from one another. More

Jan 1, 1994

By Carl R. Christiansen

Excellent underground industrial sites and warehouse facilities have been constructed in Europe and at several locations in the United States. Many quarry and mine operators are considering, or should consider, the possibilities of the development of their mineral properties in such a manner as to make underground space that is suitable for a secondary industrial use. Before proceeding with mine or quarry development, the operator should answer the following questions: 1) Is there a need for underground industrial space in your geographical area? 2) Is your deposit suitable for development of space for industrial usage? 3) If the deposit is suitable, what methods of development can be used? 4) What are the comparative economics of the different methods of space development? An honest analysis of the first two questions may eliminate the need for proceeding to the third. Affirmative answers to questions 1 and 2 should be followed by the engineering and economic studies required in response to questions 3 and 4.

Jan 1, 1975

By R. K. Singhal

The underground coal mining systems have kept pace with the developments that have occurred in other types of mining industry. A diversified group of machines with high horsepower motors, built-in microprocessor technology and with numerous options to satisfy the miners need in a varying geological environment are now available. A brief review of this existing technology and its likely status within the next 21 years is presented. Discussed also are some of the on-going advanced developments in electronic mechanization, remote control and automation together with mine wide data monitoring and management systems and facilities to process and transmit data to remote computerized stations.

Jan 1, 1989

By Farid Mirahadi

Forecasting productivity of construction operations is a difficult but crucial task in planning construction projects. Over the past decades, many models have been developed to forecast productivity for different construction operations. Models made up of several functional relations and controlled by a specific number of control rules are more in line with human reasoning and logic. Neural-Network-Driven Fuzzy Reasoning (NNDFR) structure as one of these models shows a great performance for modeling datasets among which clear clusters are recognizable. Lack of the compatibility of conventional NNDFR with fuzzy clustering algorithms besides the insufficient attention paid to the optimization of number of clusters in this model, created a potential area for further research. The main contribution of the proposed model is to develop a modified NNDFR system to model construction data. To this end, Fuzzy C-Means (FCM) algorithm is substituted for K-means in NNDFR structure, and its parameters such as the number of clusters and weighting exponent are optimized through genetic algorithm. The proposed model is further verified through simulation of a construction operation in which several qualitative and quantitative factors are considered. Its implementation to the case study shows a considerable improvement of model performance with lower Mean Squared Error (MSE). The developed model assists researchers and practitioners in utilizing historical construction data to forecast productivity of construction operations with a high accuracy that could not be obtained by traditional techniques.

Aug 1, 2013

By M. J. Laurila

On-line analyzers have made possible the use of Fuzzy Logic Control (FLC) for local control applications in coal preparation plants. This includes FLC control of complete circuits such as heavy media vessels, cyclones and froth flotation. These circuits can be controlled in real time in a feedback control loop with an on-line analyzer. Control strategies can be readily developed using Statistical Process Control (SPC) techniques which are first applied off-line in manual mode through the use of control charts and then this process is brought on-line using FLC in conjunction with an on-line analyzer to fully automate the circuit. This paper outlines the types of control strategies employed and presents examples of automatic verses manual control.

Jan 1, 1997

By M. J. Laurila

On-line analyzers have made possible the use of fuzzy logic control (FLC) for local control applications in coal preparation plants. This includes FLC of heavy media vessels, cyclones and froth flotation. These circuits can be controlled in real time in a feedback control loop with an on-line analyzer. Control strategies can be developed using statistical process control (SPC) techniques that are first applied offline in manual mode through the use of control charts. This process is then brought on line using FLC in conjunction with an on-line analyzer to automate the circuit. The advent of programmable logic controllers into preparation plants has enabled the implementation of regulatory control. As shown in Fig. 1, regulatory control is the first level of process control as applied in a processing facility. This involves: ? The logic sequences for start-up and shutdown procedures and all the necessary interlocks for safety purposes. ? The systems to control individual parameters and individual units. Various sensors provide information that is useful to plant operators, while some can be used as signals to simple control loops (Couch, 1996). This is the foundation of process control. It must be performed well if there is to be any success in supervisory control (level 2). Supervisory control involves overseeing and directing the operation of unit operations, or of the whole plant. This includes more complex loops with cascade control. And it may involve feed forward and feedback systems. There have been some applications of this kind of control to thickeners and flotation circuits in coal preparation plants. In addition, there are supervisory controls on some dense medium circuits and, in a few cases, on jigs. These are implemented with proportional integral- derivative (PID) controllers that are available in the PLC or distributed control system (DCS) operating soft ware. In a coal preparation plant, there might exist 200 to 400 PID loops. In a coal-pro¬cessing plant, this number is increased to 2,000 loops or more. It is important to use the correct algorithm or function to control a process variable to the point where automatic control shows a markedly decreased variability over manual mode. This is where fuzzy logic and neural networks have an advantage over traditional model-based expert systems. Because dynamic models of coal preparation unit operations do not exist, model-based expert systems that are prevalent in minerals processing cannot work. Not enough is known about the dynamics of the gravity separation processes employed in coal preparation. Therefore, an artificial intelligence (AI) system consisting of a subset of fuzzy logic, genetic algorithms and neural networks must be applied in coal preparation plants if a supervisory control system is to be successful across a range of feed characteristics and variable set points.

Jan 1, 1997

By T. Neesse

In many cases, the use of hydrocyclone control is desirable for the stabilization of separation in the setting of changing feed conditions. Control concepts based on exact mathematical models are not satisfactory due to the complexity of the physical process. In this case, fuzzy control is a suitable solution. The data are primarily derived from an optical sensor that monitors the outside view of the free underflow stream. A throttling valve, serving as an actuator, is installed in the overflow pipe that regulates the volume split of the cyclone. Applications in closed circuit grinding and in separation plants for tunnel driving, fine sand dewatering, and classification of kaolin demonstrate the typical use of this development. Additionally, the technological characteristics of the cyclone may be improved by this control, which is mainly caused by the increased discharge capacity of the un-der flow nozzle. A further advantage is the option to operate at an optimal operation point. In many cases, this point is located at the transition spray/rope discharge. The improved operation characteristics present new options for extensive applications of fuzzy cyclone control.

Jan 1, 2014

By Hamed Khodadadi, Hamid Ghadiri

The ball mill grinding circuit has widespread application in mining, metallurgy, chemistry, pharmacy and research. It faces some challenges because a grinding circuit is a multivariable system in which high interaction between loops, variation of system parameters with time, and time delays are problems. In this study, a fuzzy logic self-tuning proportional–integral–derivative (FLST-PID) controller based on an improved disturbance observer is designed for control of ball mill grinding circuits. It is combined with an improved disturbance observer (IDOB) to eliminate system interaction, attenuate internal and external disturbances and compensate the effect of system uncertainty on the performance of the ball mill grinding circuit.

By Hamed Khodadadi, Hamid Ghadiri

In this study, a fuzzy logic self-tuning PID controller based on an improved disturbance observer is designed for control of the ball mill grinding circuit. The ball mill grinding circuit has vast applications in the mining, metallurgy, chemistry, pharmacy, and research laboratories; however, this system has some challenges. The grinding circuit is a multivariable system in which the high interaction between loops, the variation of the system parameters with time, and time delay are some of the problems that pose a challenge. Since the controller parameters are determined offline in classic PID control, these gains are unchangeable and cannot overcome the mentioned challenges in this system. Hence, a fuzzy logic self-tuning PID controller, which is a combination of fuzzy logic and a conventional PID controller, is proposed to control the grinding system, especially in the presence of model mismatch and disturbances. In addition, in order to solve the system challenges, a multivariable control approach based on an improved disturbance observer is proposed to suppress the effects of the disturbances. The most important feature of the algorithm proposed in this paper as the combination of fuzzy logic self-tuning PID and improved disturbance observer is its ability to eliminate system interaction, attenuate internal and external disturbances, and compensate the effect of system uncertainty on the performance of the ball mill grinding circuit. Simulation results in the cases of the set-point change in particle size and circulating load in the presence of model mismatch and external disturbances confirmed the controller performance compared to other controllers.

By J. A. Meech, C. A. Harris

"The application of control theory in mineral processing is more difficult than in other industries because of the complex nature of the unit processes involved and because of problems with accurate on stream measurement of process variables. Conventional control is based on proportional, integral and derivative functions of a continuously measured error term. Computer control can enhance these actions by incorporating logical routines to switch from one relationship to another. The success of this logical approach depends on our understanding of the process dynamics and the stability of the process and model under all conditions. Typically the model does not apply at all times in mineral processing because of frequent and unmeasurable changes in the ore parameters.Recent advances in the theory of fuzzy sets have led to the application of this science to process control. Fuzzy Logic can be used to develop heuristic or rule-of-thumb controllers with the strategy based on the actual operating practice of experienced plant operators. Control action has increased flexibility through the adaptation of human reasoning. Acceptance of the control system by operating personnel is significantly higher because of their participation in its formulation. The requirement of an exact model is not essential.A heuristic controller has been designed and tested with a computer simulation model of a secondary crushing plant. The results of this study are discussed and future applications of this control technique to other mineral processes are suggested. IntroductionThe application of control theory in mineral processing is more difficult than in other industries because of the complex nature of the unit processes involved. Mineral processes typically are characterized by non-linear relationships between input and output variables. Many of these variables cannot be monitored accurately on-stream and so long time lags on the measurement loop are features of the system. The processes, themselves, often have long time-varying responses while the process loads fluctuate significantly on a short-term basis.Attempts to control these processes have led to the formulation of mathematical models to describe each unit activity. Adaptive techniques have also been tried to compensate and account for process changes and vageries. These approaches are mathematically rigorous so that their complexity and precision limit their usefulness when applied to ""vague"" processes."

Jan 1, 1987

By M J. Pejovic, I Miljanovic, A Milutinovic4, T Benovic, A Petrovski

The paper presents a model of a multigrade monitoring-management structure for support to decision making and management in real and extended time in mineral processing (MP). The model was created as a result of a long-lasting research, design and development of mining, computer integrated monitoring-management systems. Apart from the general explanations, the authorsÆ state in the introduction that efficiency of a system for support to decision-making and management in mineral processing is more difficult to achieve by conventional approaches, than by the fuzzy logic approach. Starting from the multiphase structure of process flows in MP, the following are process and monitoring-management oriented graphs. The graphs served as a foundation of the multigrade hierarchical fuzzy model for support to decision making and management in MP. Following the example of the monitoring-management system of the æRudnikÆ mine flotation plant, fuzzy logic implementation was shown. The key conclusions of the paper are that fuzzyfication of layers of the decision making and management model has full justification due to the complexity and dynamics of mineral processing processes, complications and often insurmountable difficulties concerning the precise description of real systems by conventional mathematical tools, variability of external influences, and the (general) non-linearity of the MP processes management criteria functions.

Sep 26, 2011

By C. L. Karr

Researchers at the University of Alabama have developed a method for producing fuzzy linguistic models of mineral processing equipment directly from engineering data. These fuzzy linguistic models rely exclusively on data collected from the processing systems being modeled and do not presuppose an understanding of the physics of the system. The fuzzy linguistic models use descriptive rules and explicit membership functions that provide a precise, nonmathematical description of the processing equipment. A genetic algorithm is employed to simultaneously select rules and tune membership functions used in the fuzzy models. The result is an extremely flexible approach to modelling that is applicable in a variety of linear and nonlinear systems. The effectiveness of this approach to modelling is demonstrated using a four-input, two-output model of a grinding circuit.

Jan 1, 1996

By Cong Zhang, Huaying Wang, Yixin Wei

"Water inrush is a serious geological accident in underground coal mines. This paper focuses on the method of the bow tie analysis based on fuzzy reliability to assess the risk of water inrush in coal mines. First, post failure probability and repair probability of initiating events are divided into 5 levels. Then triangular fuzzy numbers are adopted to quantify experts’ language and to acquire the reliability rate which close to the actual values by defuzzification and calculation. According to dynamic bow-tie analysis model, using the method of moments to fit the reliability time of events by Weibull distribution and offering the random sampling rule of failure and repair time for illustrating the feasibility of fuzzy reliability evaluation. To demonstrate the effectiveness of the proposed assessment approach, bow tie analysis model of water inrush in coal mines is taken as an example.Introduction Dynamic bow tie (DBT) analysis is composed of dynamic fault tree and dynamic event tree analysis, and considers the impact of the time factor upon risk assessment of a system. There are many algorithms applied to calculation of the probabilities of node accident and accident consequence of dynamic bow tie analysis: Hidden Markov Model, Bayesian Network (Khakzad et al 2013), Integral Algorithm (Amari et al 2003) and Monte Carlo Simulation (Kim et al 2016). In terms of simulated time and practicability, the Monte Carlo Simulation has an advantage over other methods. DBT requires mass data in quantitative analysis, including the failure rates and the repair rates of the basic events of the Fault Tree (FT) and the subsequent events of the Event Tree (ET) at different time points, i.e., the distribution of failure time and repair time. In practical analysis, it is hard to obtain a large amount of exact historical statistical data, which is a major problem of risk assessment. Due to the difficulty of obtaining the exact data and historical failure data of the basic events and the subsequent events, the FT and ET analysis is stuck with the study of minimal cut sets, minimal diameter sets, structural importance and qualitative analysis (Liu and Zhang 2010, Yan et al 2012, Wang et al 2009, Li and Wang 2011). This paper will use fuzzy numbers and the defuzzification method to transform the experts’ language into the failure rates and repair rates of basic events and subsequent events, solving the problem that it is difficult to obtain a large amount of historical statistical data, and will use the method of moment to conduct Weibull fitting of the reliability time to provide the random sampling criteria of event failure and repair time in Monte Carlo simulation."

Jan 1, 2017

By Flavio Rojos-Tapia, Oscar Pereira-Cerda, Samuel Sánchez-Pino, Samuel Sánchez-Baquedano

"Pneumatic flotation was introduced to the Chilean Copper Mining Industry in 1993 by Ingeniería de Minerales S.A. (IDM). The technology is based on the designs of Dr. Rainer Imhof from Germany, who is the designer of several different types of pneumatic flotation cells, already sold through his Company Maelgwyn Mineral Service Limited (MMH). The company is represented by Ingenieria de Minerales S.A. (IDM) in South America.Pneumatic flotation, has been used in tough industrial applications .It has been successfully used for metallic ores such as copper sulphide and oxide minerals, copper slag, silica and silicates from iron magnetic preconcentrate (reverse flotation) and gold. It has also provided promising results when applied to molybdenum flotation. The latest applications, with ultrafine molybdenum particles in operating plants, is showing the V and G Cell (end model designed) as a real technological alternative to conventional flotation., The G Cell is an extremely high speed flotation machine with high selectivity which introduces the possibility of producing a final molybdenum concentrate with only one stage of cleaning. This is a completely new development in molybdenum flotation in the industrial circuit which has the potential to dramatically reduce the circulating load in the cleaning circuit. As a consequence the capital costs of future Molybdenum plants may also be reduced. The suitability of the G Cell will have to be determined on a case by case basis but it provides the metallurgist with an alternate flowsheet for consideration.The good performance of the G Cell can be explained by the high gas hold-up and very effective micro-turbulence which helps improve the attachment of solid particles to the bubbles. This technology may change our traditional concept of residence time in flotation. Additionally, the rotation phenomena introduced in the vessel of the G Cell ,creates radial separation forces which are critical to achieving a more rapid separation of the target minerals from the tailing. This results in a much reduced residence time requirement in the flotation machine. Some benefits associated with the use of the new G Cell are: less energy consumption, less maintenance costs, simple and reliable circuit to operate and a small area required for installing the circuits.As a result of the industrial experience in the Chile, the pneumatic flotation type G Cell can be regarded as a technology which must be considered as a replacement technology for the rougher and cleaner stages for fine particle flotation."

Jan 1, 2008

By AIME AIME

MOST recently elected to the limited group of Honorary Members in the A.I.M.E. is the distinguished Australian metallurgist, Guillaume Daniel Delprat. His citation reads: "in recognition of his distinguished achievement as metallurgist, engineer, and administrator in the production of ferrous and nonferrous metals," Mr. Delprat's ability and experience in both the ferrous and nonferrous fields at once distinguishes him from most of his professional brothers. Mr. Delprat's nativity was neither Australian nor English, for he was born in Delft, Holland, in 1856, and educated in Amsterdam. At the age of 22 he went to Spain, as metallurgist for the Tharsis Sulphur and Copper Co., Ltd. Afterwards he spent some time with the Bede Metal and Chemical Co., which had mines in both Spain and Norway, and of which company he became general manager. Other positions of responsibility held by Mr. Delprat before he went to Australia included the managing directorship of the Cordova Exploration Co., with properties in Spain and Canada; of the Rincon Silver-Lead Mining Co., in Spain; and of the Deloro Gold Mines, in Canada.

Jan 1, 1936

Gaby Copper Mining?s Gabriela Mistral property is located in the Antofagasta region of northern Chile, at an altitude of 2,660 m (8,727 ft) above sea level. The reserve contains an estimated 562 Mt (620 million st) of oxide ore with an average grade of 0.41 percent total copper. The mine went into production in 2008. Gaby Copper faced the problem of having no reliable way to measure the solids level. This is a challenge that exists throughout the mining industry, where dust in the air and accumulation of solids on a sensor make accurate measurements difficult in areas such as transfer chutes, the rock box underneath crushers, silos and anywhere else that information is needed on the level of solids. The next-generation technology in the Sitrans LR560 radar from Siemens addresses this challenge. With a frequency of 78 GHz ? higher than previous generations of radar ? it provides a more robust signal for measuring in areas where there are high levels of dust accumulation. The Sitrans LR560 provides a signal beam angle of four degrees, significantly narrower than any other product on the market can offer.

Jan 1, 2014

By A. Mcdonald, F. W. Breaks, T. F. Morris, S. A. Averill, D. C. Crabtree

Abstract-Gahnite, a zinc-bearing spinel, is a resistate mineral that may be used as an indicator mineral of polymetallic deposits in high-grade metamorphic terrain. The Ontario Geological Survey recently completed surficial mapping and sampling programs in the Separation Lake area of northwestern Ontario and Kinniwabi Lake area of northeastern Ontario in which gahnite was recovered from samples of surficial sediments. Ternary plots of the composition (ZnO, MgO, FeO[t]) of gahnite recovered from these surficial studies reveal three distinct groups: Group 1 is characterized by low (< 1 wt%) MgO values; Group 2 by higher (>1 wt%) MgO values; and Group 3 by higher FeO(t) values than Groups 1 and 2. The composition of in situ gahnite recovered from volcanogenic massive sulfide mineralization, Zn-rich Sedex-type mineralization and peraluminous rare-element mineralized granite and pegmatite also was determined. The composition of the gahnite obtained from surficial samples was compared with that of in situ material. Gahnite from the peraluminous rareelement granite and pegmatite overlapped very well with surficial gahnite of Group 1. Gahnite from volcanogenic massive sulfide mineralization and Sedex-type mineralization overlapped well with surficial gahnite of Group 2. These results suggest that determination of gahnite composition in indicator mineral surveys may be useful in exploration programs when assessing the mineral potential of a region.

Jan 1, 1997

By A. Mcdonald, F. W. Breaks, T. F. Morris, S. A. Averill, D. C. Crabtree

Gahnite, a zinc-bearing spinel, is a resistate mineral that may be used as an indicator mineral of polymetallic deposits in high-grade metamorphic terrain. The Ontario Geological Survey recently completed sur?cial mapping and sampling programs in the Separation Lake area of north-western Ontario and Kinniwabi Lake area of northeastern Ontario in which gahnite was recovered from samples of sur?cial sediments. Ternary plots of the composition (ZnO, MgO, FeO[t]) of gahnite recovered from these sur?cial studies reveal three distinct groups: Group 1 is characterized by low (< 1 wt%) MgO values; Group 2 by higher (>1 wt%) MgO values; and Group 3 by higher FeO(t)values than Groups 1 and 2. The composition of in situ gahnite recovered from volcanogenic massive sul?de mineralization, Zn-rich Sedex-type mineralization and peraluminous rare-element mineralized granite and pegmatite also was determined. The composition of the gahnite obtained from sur?cial samples was compared with that of in situ material. Gahnite from the peraluminous rare-element granite and pegmatite overlapped very well with sur?cial gahnite of Group 1. Gahnite from volcanogenic massive sul?de mineralization and Sedex-type mineralization overlapped well with sur?cial gahnite of Group 2. These results suggest that determination of gahnite composition in indi-cator mineral surveys may be useful in exploration programs when assessing the mineral potential of a region.

Jan 1, 1997